Designing of Bayesian Multiple Deferred State Sampling Plan Based on Gamma–Poisson Distribution

Balamurali, S.; Jeyadurga, P.; Usha, M.

doi:10.1080/01966324.2015.1086708

Cited by 37 publications

(15 citation statements)

References 10 publications

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“…The ARL measure for the chart performance is studied by many authors including . The MDS sampling scheme has been utilized in the SPC by many authors including Ahmad et al, Aslam et al, Azam et al, Khan et al, and Knoth …”

Section: Introductionmentioning

confidence: 99%

Design of a t‐chart using generalized multiple dependent state sampling

Aslam

Raza

Ahmad

2019

Quality & Reliability Eng

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In this article, a new t-chart based on generalized multiple dependent state (GMDS) sampling is proposed for efficient monitoring of a process by assuming that the time between events follows the exponential distribution. The proposed t-chart has two pair of control limits and utilizes the past sample information with the current sample information. The control chart coefficients are estimated by considering different values of the in-control average run lengths. The proposed t-chart is compared with the existing chart by using the out-of-control average run length and extra quadratic loss function. The comparison reveals that the proposed charting strategy has better shift detection ability in process mean. An illustrative example is given for the practical implementation of the proposed chart.

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Section: Introductionmentioning

confidence: 99%

Design of a t‐chart using generalized multiple dependent state sampling

Aslam

Raza

Ahmad

2019

Quality & Reliability Eng

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“…The quality based coefficient of variation and non-linear optimization model is used to solve the parameters of the developed MDS plan by Yan et al [5]. Based on Bayesian methodology S.Balamurali [6] proposed the MDS plan using Gamma poison distribution. Saminathan Balamurali [7] developed the MDS plan based on current and successive lot sample information, the product quality is measured by median life.…”

Section: A Review Of the Lecturermentioning

confidence: 99%

Designing Optimal Multiple Deferred State Mds–1 Sampling Plan using Truncated Poisson Distribution

Subramani¹,

Ambika²,

Venugopal³

2019

IJITEE

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The producer and the consumers show their interest in accepting the lot with good quality by checking the lot with minimum sample size. In this paper for given Acceptance Sampling Limit and Limiting Quality Limit we have designed the multiple deferred sampling plans using Truncated Poisson distribution to minimize the risk by considering the sample size in account. Here overall risk for wrong decision is considered as optimization criteria. Tables and procedures are derived using Truncated Poisson distribution and also it is compared with the existing Poisson distribution to find optimum result.

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“…Some of the authors studied the MDS sampling plan for both attribute inspection and variables inspection. For the attribute MDS sampling plan, one may refer to Vaerst, 15 Soundararajan and Vijayaraghavan, 16 Govindaraju and Subramani, 17 Subramani and Haridoss, 18 Balamurali et al 19,20 For variables inspection, one may refer to Balamurali and Jun, 21 Aslam et al 22 and Wu and Wang. 23 Nowadays, MDS sampling is also applied for designing the control charts (see, for example, Aslam et al 24,25 ).…”

Section: Introductionmentioning

confidence: 99%

An Attribute np Control Chart for Monitoring Mean Life Using Multiple Deferred State Sampling Based on Truncated Life Tests

Balamurali

Jeyadurga

2019

Int. J. Rel. Qual. Saf. Eng.

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In this paper, we design an attribute [Formula: see text] control chart for monitoring the mean life of the product where the lifetime follows the Pareto distribution of the second kind. The lifetime of the product is determined by time truncated life test and the multiple deferred state sampling is used to declare the status of the manufacturing process. Control limit coefficients and multiple deferred state sampling parameters such as sample size and number of successive subgroups required to declare the state of the process are determined such that the in-control average run length is as near as possible to the target average run length. Out-of-control average run lengths are calculated for the determined parameters using various shift constants. The performance of the chart is compared with other existing chart in terms of average run length.

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Designing of Bayesian Multiple Deferred State Sampling Plan Based on Gamma–Poisson Distribution

Cited by 37 publications

References 10 publications

Design of a t‐chart using generalized multiple dependent state sampling

Design of a t‐chart using generalized multiple dependent state sampling

Designing Optimal Multiple Deferred State Mds–1 Sampling Plan using Truncated Poisson Distribution

An Attribute np Control Chart for Monitoring Mean Life Using Multiple Deferred State Sampling Based on Truncated Life Tests

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